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Record W2184589704

Northern Watershed Ecosystem Response to Climate Change (North-Watch) - Towards a comparative ecohydrology of northern catchments.

2012· article· en· W2184589704 on OpenAlexaboutno aff
Doerthe Tetzlaff, Chris Soulsby, J. M. Buttle, Sean K. Carey, Hjalmar Laudon, Jeffrey J. McDonnell, K. J. McGuire, Jan Seibert, James B. Shanley

Bibliographic record

VenueEGU General Assembly Conference Abstracts · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicHydrology and Watershed Management Studies
Canadian institutionsnot available
Fundersnot available
KeywordsSnowmeltClimate changeEnvironmental scienceWatershedStreamflowEcohydrologyEcosystemPrecipitationEnvironmental changeSnowClimatologyPhysical geographyDrainage basinEcologyGeographyOceanographyGeology
DOInot available

Abstract

fetched live from OpenAlex

In few places will the changes and challenges associated with climatic change be greater than in the circumpolar mid-high latitudes of the northern hemisphere. Slight temperature differences determine whether precipitation falls as rain or snow, and the degree to which winter snow packs accumulate and the rate at which they subsequently melt. This has implications for stream flow regimes, water quality and in-stream hydroecology. The Northern Watershed Ecosystem Response to Climate Change (North-Watch) programme is an international interdisciplinary inter-site comparison project spanning a transect of hydro-climatic zones in Scotland, the USA, Canada and Scandinavia. The overall aim is to better understand the integrated consequences of climate change on the physical, chemical and biological characteristics of water resources across northern regions. Here, we present initial findings from these analyses. The way in which hydroclimatic drivers interact with catchment characteristics are examined to show how the synchroneity, resistance and resilience of input-output responses varies spatially and temporally across sites. The dominant influence is the nature of the snowmelt period and how strongly this influences the hydrological regime. Linked to this is the variable nature of the threshold response of input ‐ streamflow dynamics and how this changes for rainfall and snowmelt events. The ways in which these hydrological controls regulate Carbon fluxes from different catchments are also explored, and the implications for in-stream ecosystem response assessed. As the hydroclimatic drivers influencing the catchments are changing in a warming climate, vegetation and soil are also likely to change. This in turn will affect patterns of partitioning, storage and release of water with associated changes in streamflow dynamics. Budyko Curves are used to examine the current differences between the North-Watch catchments in terms of water and energy limitations, and likely future trajectories given climatic change scenarios. This highlights the sensitivity of certain catchments and underlines the need for integrating ecological concepts into hydrological classification schemes.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.041
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.003

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.047
GPT teacher head0.276
Teacher spread0.229 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2012
Admission routes1
Has abstractyes

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